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Record W4285023697 · doi:10.1038/s41467-022-31226-2

Reply to: Questioning whether the IgM Fc receptor (FcμR) is expressed by innate immune cells

2022· letter· en· W4285023697 on OpenAlexaff
Shawn P. Kubli, Parameswaran Ramachandran, Gordon S. Duncan, Rich Brokx, Tak W. Mak

Bibliographic record

VenueNature Communications · 2022
Typeletter
Languageen
FieldImmunology and Microbiology
TopicT-cell and B-cell Immunology
Canadian institutionsUniversity of TorontoPrincess Margaret Cancer Centre
Fundersnot available
KeywordsInnate immune systemImmune systemHaematopoiesisExpression (computer science)Computational biologyGene expressionReceptor expressionGenetic dataReceptorImmunologyMedicineBiologyComputer scienceGeneCell biologyStem cellInternal medicineGenetics

Abstract

fetched live from OpenAlex

The Matters Arising submission from Skopnik et al. is a comparative analysis of single-cell RNA sequencing (scRNAseq) data obtained from two groups 1 , 2 . The submission highlights the well-documented limitation of scRNAseq technology, termed “dropout events”, that result in zero detected reads for some genes despite alternative evidence of their expression 3 , 4 , 5 . The submission further debates a hypothesis relating to Fcmr expression within the hematopoietic system. The authors highlight negative data for Fcmr expression in myeloid cells as it relates to reported expression data in innate immune cells from various groups. This debated point of Fcmr expression is further detailed in a review by Wang et al. 6 .

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.027
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.023
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0020.003
Scholarly communication0.0020.004
Open science0.0020.002
Research integrity0.0270.033
Insufficient payload (model declined to judge)0.0040.008

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.252
Teacher spread0.240 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2022
Admission routes1
Has abstractyes

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